2. A random sample of 30 warehouses was selected as part of a study on electricity usage, and the number of kilowatt-hours (kWh) was recorded for each warehouse in the sample for the March quarter of 2019. The average usage was found to be 375kWh. In a very large study in the March quarter of the previous year it was found that the standard deviation of the usage was 81kWh. It is believed that the standard deviation may have changed from the previous year. From the small data set in 2019, the sample standard deviation is 91.5kWh. Assuming that the usage is normally distributed, calculate a 99% confidence interval for the mean usage in the March quarter of 2019.
2. A random sample of 30 warehouses was selected as part of a study on electricity usage, and the number of kilowatt-hours (kWh) was recorded for each warehouse in the sample for the March quarter of 2019. The average usage was found to be 375kWh. In a very large study in the March quarter of the previous year it was found that the standard deviation of the usage was 81kWh. It is believed that the standard deviation may have changed from the previous year. From the small data set in 2019, the sample standard deviation is 91.5kWh. Assuming that the usage is normally distributed, calculate a 99% confidence interval for the mean usage in the March quarter of 2019.
2. A random sample of 30 warehouses was selected as part of a study on electricity usage, and the number of kilowatt-hours (kWh) was recorded for each warehouse in the sample for the March quarter of 2019. The average usage was found to be 375kWh. In a very large study in the March quarter of the previous year it was found that the standard deviation of the usage was 81kWh. It is believed that the standard deviation may have changed from the previous year. From the small data set in 2019, the sample standard deviation is 91.5kWh. Assuming that the usage is normally distributed, calculate a 99% confidence interval for the mean usage in the March quarter of 2019.
2. A random sample of 30 warehouses was selected as part of a study on electricity usage, and the number of kilowatt-hours (kWh) was recorded for each warehouse in the sample for the March quarter of 2019. The average usage was found to be 375kWh. In a very large study in the March quarter of the previous year it was found that the standard deviation of the usage was 81kWh. It is believed that the standard deviation may have changed from the previous year. From the small data set in 2019, the sample standard deviation is 91.5kWh. Assuming that the usage is normally distributed, calculate a 99% confidence interval for the mean usage in the March quarter of 2019.
Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...
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